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Transcript
Catastrophic Risks and
Insurance: Financial Designs and
Market Capacity
Mike Orszag
March 2005
Catastrophic Risks
Richard Posner, Catastrophe: Risk and Response, Oxford,
2004
• Natural disasters:
– Asteroid hits the planet
– Hurricanes, tornadoes
• Man-made disasters:
– Particle accelerate creating a strange particle which crushes
the planet into a ball 100 metres across
– Terrorism
– Global warming
• Others
– Mortality risk
Life Insurance and Pension
Catastrophes
• Tremendous uncertainty about future
longevity
• Vaupel: life expectancy at 65 may rise
without bound
• Olshansky: life expectancy may decrease
– no natural limit but no reason for
individuals to live a long time
Life Insurance and Pension
Catastrophes
25
20
15
10
5
0
19
50 954 958 962 966 970 974 978 982 986 990 994 998
1 1 1 1 1 1 1 1 1 1 1 1
Annuity Factor Constant Interest Rate
Annuity Factor - Real
Denmark
Grosen and Jorgensen, Journal of Pension Economics and Finance,
1(3), 2003
Insurability
• Available data and information
• Locality of risk (geographic?)
• Moral hazard:
– Preparation
– Possibility of human influence on event
The Capacity Puzzle
• Global equity markets significant in size. If
insurance products have high rates of
return, capital should flow into insurance
sector….
• … yet even products considered
insurable limited in quantity
Capacity Potential
Source: Mechler (IIASA), 2004
The Capacity Puzzle
• Are catastrophe products zero beta
(Froot/Posner)?
• Auffret (2003) – looked at Caribbean countries
– premia 1.5% of GDP 1970-1999 whereas
claims average 0.5% of GDP.
• Explanations: catastrophes not zero beta
• Explanations: basis risk?
• Is there scope for government involvement in
market?
Measuring Capacity
• Cummins, Doherty and Lo, “Can Insurers
Pay for the Big One?”, Journal of Banking
and Finance (2002)
• Are losses of US$100 bn sustainable?
• Comparisons:
– Northridge Earthquake US$10bn
– Hurricane Andrew US$19bn
Conceptual Framework
Payouts
Perfect
market
Capacity in
practice
Losses
Measuring Capacity
• Is capital distributed optimally? Optimal
portfolio close to all having share in
aggregate losses.
• Reinsurance priced on correlation of
individual losses with aggregate losses
• Normally distributed losses
• Pricing assumed competitive
• No transaction costs
Results
Correlation
All US
0.18
Florida
0.13
Industry could cover 90-96% of $100 bn loss
Comments
• Does not get at question: how much can
industry afford to write?
• Estimation based on all losses instead of
catastrophic losses (less scope for
reinsurance)
Comments
Payouts
Perfect
market
Better financial markets
More demand for
security
Less friction in
reinsurance
More competitive
markets
Capacity in
practice
Losses
Solutions for more market capacity
• Risk sharing designs, in particular with
public sector (may need international
involvement)
• Public benchmark securities
Issues in non-OECD countries
• Low penetration but some success stories
(Turkey earthquake insurance)
• Governments themselves may face
significant risks and therefore may want
to set up contingent financing or prefund
Summary
• Capacity issues are apparent, even
though theory suggests they should not
be
• Lack of successful large-scale pure
private sector solutions
• Need to consider public-private
partnerships both in OECD and nonOECD countries